This proposal is a continuation of a Merit Grant whose long-term objective has been the development of powerful analytical and micropreparative separation tools for bioanalysis. Our specific goal now is the development of an integrated discovery platform for a comprehensive, global view of differential protein expression. We will study and advance the newly introduced "shot-gun" approaches to protein expression analysis (ICAT), using the following or a related sequence of steps: prefractionation of two proteomes separately, isotopic labeling, digestion, pooling, and separation/MS analysis. We shall develop novel chemistries and microfabricated separation tools for this effort. For prefractionation, we will focus on solution IEF in the form of a series of chambers with immobiline pH control on membranes separating the chambers or coated on the walls of the chambers. The former will be used for large scale protein prefractionation (10-50 mg) for low copy number expression and the latter for multiple chambers of 30 muL each in volume for high throughput and narrow pI range prefractionation. With respect to the chemistries to be employed, besides sulfhydryl reaction, we will use isotopic labeling of phosphate and N-terminal residues, the latter for comprehensive labeling of peptide fragments. Affinity approaches will be used in the analysis of glycosylation. The separation and mass spectroscopic analysis of the thousands of peptides will be accomplished using microfabricated multichannel 1 and 2 dimensional (LC/CE) high throughput separation devices, coupled off-line to MALDI targets. The resultant separation streaks will be analyzed by a very high throughput MALDI/TOF instrument (2k Hz laser) (being developed on another NIH grant). Novel microfabricated structures will be developed for separation, liquid pumping, automated sample loading, etc. We will use standard yeast samples to develop the technology, followed by relevant proteome samples, as provided by our collaborators. The various chemistries and separation devices will be integrated into discovery of global protein expression patterns in various relevant biological states.